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Found 127 Skills
Spatial organization of knowledge in navigable directories
Build a personal knowledge wiki from your notes, journals, and documents. LLM ingests data, synthesizes cross-linked Wikipedia-style articles, and serves a web UI.
Use when the agent needs access to information beyond its training data — knowledge sources, RAG pipelines, or grounding data.
Build and maintain a personal knowledge base using Karpathy's llm-wiki methodology across Claude Code, Codex, and OpenClaw agents.
Process raw source documents into wiki pages. Use when the user adds files to raw/ and wants them ingested, says "process this source", "ingest this article", "I added something to raw/", or wants to incorporate new material into their wiki, second brain, or knowledge base.
Maintain a reviewable LLM Wiki from immutable raw notes, including ingest planning, querying, linting, and guarded raw Graphify maps that help agents generate better wiki pages.
Use when a complex MEL/SRHR task requires deep evidence synthesis before planning begins. Triggered by Ann between PHASE 1 and PHASE 2 for COMPLEX tasks, or directly by Ane for standalone literature reviews.
Organize research, discussions, and exploratory content into systematic knowledge documents, or collect and organize research information about companies/products. Use this skill when users request knowledge summarization, note organization, knowledge base document generation, or structuring discussion content into formal documents. It also applies to collecting and organizing research information about AI companies, startups, and products. Even if users don't explicitly mention "knowledge graph" or "knowledge base", this skill should be used for any workflow that involves sorting scattered information into systematic documents.
Use when bootstrapping a new personal wiki for any knowledge domain — research, codebase documentation, reading notes, competitive analysis, or any long-term knowledge accumulation project.
Use when asking a question against a personal wiki built with wiki-init and wiki-ingest. Do not answer from general knowledge — always read the wiki pages first.
Create narrative lore entries that transform technical work into mythological stories. Use when generating agent memory, documenting changes as narrative, or building persistent knowledge through storytelling.
Self-evolving context protocol that captures insights, prevents repeated mistakes, and evolves project documentation through structured feedback loops.